Abstract
Nowadays, given the technological advance in CT imaging and increasing heterogeneity in characteristics of CT scanners, a number of CT scanners with different manufacturers/technologies are often installed in a hospital centre and used by various departments. In this phantom study, a comprehensive assessment of image quality of 5 scanners (from 3 manufacturers and with different models) for head CT imaging, as clinically used at a single hospital centre, was hence carried out. Helical and/or sequential acquisitions of the Catphan-504 phantom were performed, using the scanning protocols (CTDIvol range: 54.7–57.5 mGy) employed by the staff of various Radiology/Neuroradiology departments of our institution for routine head examinations. CT image quality for each scanner/acquisition protocol was assessed through noise level, noise power spectrum (NPS), contrast-to-noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD) and non-uniformity index analyses. Noise values ranged from 3.5 HU to 5.7 HU across scanners/acquisition protocols. NPS curves differed in terms of peak position (range: 0.21–0.30 mm-1). A substantial variation of CNR values with scanner/acquisition protocol was observed for different contrast inserts. The coefficient of variation (standard deviation divided by mean value) of CNR values across scanners/acquisition protocols was 18.3%, 31.4%, 34.2%, 30.4% and 30% for teflon, delrin, LDPE, polystyrene and acrylic insert, respectively. An appreciable difference in MTF curves across scanners/acquisition protocols was revealed, with a coefficient of variation of f50%/f10% of MTF curves across scanners/acquisition protocols of 10.1%/7.4%. A relevant difference in LCD performance of different scanners/acquisition protocols was found. The range of contrast threshold for a typical object size of 3 mm was 3.7–5.8 HU. Moreover, appreciable differences in terms of NUI values (range: 4.1%-8.3%) were found. The analysis of several quality indices showed a non-negligible variability in head CT imaging capabilities across different scanners/acquisition protocols. This highlights the importance of a physical in-depth characterization of image quality for each CT scanner as clinically used, in order to optimize CT imaging procedures.
Highlights
In recent years, the extraordinary technical advances in x-ray computed tomography (CT) have largely increased its use in the clinical practice
Given that CT imaging represents the largest source of population exposure to ionizing radiation in industrialized countries [4, 5] and increased radiation dose may increase the risk of cancer [6], it is important to minimize radiation dose through an optimization and standardization of acquisition protocols [7,8,9]
This quantitative approach has been applied to the images of a typical routine abdominal protocol, which were reconstructed with the standard filtered back projection (FBP) and the Iterative Reconstruction in Image Space (IRIS) algorithm
Summary
The extraordinary technical advances in x-ray computed tomography (CT) have largely increased its use in the clinical practice. Zhang et al [9] have developed a CT protocol optimization platform by combining task-based detectability calculations with a graphical user interface that demonstrates the trade-off between dose and image quality. Their platform can be used to improve individual dose efficiency and acquisition protocol consistency across various patient sizes and CT scanners. Berta et al [19] have described a method to objectively evaluate image quality when new clinical protocol performances must be compared with a standard reference This quantitative approach has been applied to the images of a typical routine abdominal protocol, which were reconstructed with the standard filtered back projection (FBP) and the Iterative Reconstruction in Image Space (IRIS) algorithm. Noferini et al [21] have proposed and validated a method that employs a Channelling Hotelling model Observer in a CT protocol optimization program, with the aim at assuring that scanners are working at their own best with regard to image quality and patient exposure
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